07.07.2022 - 02:08

# Researchers at a large nutrition and weight management company are trying to build a model to predict a person’s body fat percentage from an array of variables such as body weight, height, and body me

Question:

Researchers at a large nutrition and weight management company are trying to build a model to predict a person’s body fat percentage from an array of variables such as body weight, height, and body measurements around the neck, chest, abdomen, hips, biceps, etc. A variable selection method is used to build a simple model. SPSS output for the final model is given below.

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .9214 .8489 .842 3.4369
ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression Residual Total 3053.290 543.379 3596.670 2 46 48 1526.645 11.813 129.239 .000
Coefficients
Unstandarized Coefficients Standarized Coefficients t Sig
B std.Error Beta
1 (Constant) Weight Abdomen circumference -53.954 -.162 1.105 4.742 .038 .101 -.525 1.355 -11.379 -4.230 10.912 .000 .000 .000

What is a 90% confidence interval for {eq}beta_1 {/eq}, the coefficient of weight, based on these results?

a. {eq}0.162 pm 4.230 {/eq}

b. {eq}0.162 pm 0.525 {/eq}

c. {eq}0.162 pm 0.064 {/eq}

d. {eq}0.162 pm 0.03 {/eq}